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Emacs-tramp-RPC: high-performance TRAMP back end using MsgPack-RPC

https://github.com/ArthurHeymans/emacs-tramp-rpc
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Nintendo Wii Themed Portfolio

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Ask HN: Why doesn't Netflix add a “Theater Mode” that recreates the worst parts?

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Just Started Using AmpCode

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LLM as an Engineer vs. a Founder?

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Crosstalk inside cells helps pathogens evade drugs, study finds

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https://huesly.app
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Toroidal Logit Bias – Reduce LLM hallucinations 40% with no fine-tuning

https://github.com/Paraxiom/topological-coherence
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Top AI models fail at >96% of tasks

https://www.zdnet.com/article/ai-failed-test-on-remote-freelance-jobs/
5•codexon•22m ago•2 comments

The Science of the Perfect Second (2023)

https://harpers.org/archive/2023/04/the-science-of-the-perfect-second/
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Bob Beck (OpenBSD) on why vi should stay vi (2006)

https://marc.info/?l=openbsd-misc&m=115820462402673&w=2
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https://github.com/dchrty/glimpsh
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Implementing TCP Echo Server in Rust [video]

https://www.youtube.com/watch?v=qjOBZ_Xzuio
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LicGen – Offline License Generator (CLI and Web UI)

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Service Degradation in West US Region

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Warcraftcn/UI – UI component library inspired by classic Warcraft III aesthetics

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Velocity of Money

https://en.wikipedia.org/wiki/Velocity_of_money
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Stop building automations. Start running your business

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Open in hackernews

What is the minimum hardware to run 671B DeepSeek 3.1

2•roscas•5mo ago
URL for Ollama is https://ollama.com/library/deepseek-v3.1/tags

So has anyone put this model to run and with what hardware?

Comments

bigyabai•5mo ago
There is no minimal hardware besides the basic requirements of being able to store/load the weights for inference.
roscas•5mo ago
Error: 500 Internal Server Error: model requires more system memory (34.1 GiB) than is available (27.2 GiB)

This is ollama run deepseek-r1:70b with size of 43gb.

32GB desktop.

magicalhippo•5mo ago
Yes, as GP said you'll need enough memory to load the weights (and KV cache).

Beyond that it's just how fast you want to go. Pure CPU will be slow, but will work. There has been a few stories and comments here[1] about people running this model.

[1]: https://hn.algolia.com/?q=671B+DeepSeek